Tag Archives: climate

Collaborative Climate Adaptation Planning for Urban Coastal Flooding

PIs:  Philip Orton, Alan Blumberg, Peter Rowe (New Jersey Sea Grant Consortium), Tanya Marione-Stanton (Jersey City Department of City Planning); Partners:  Sergey Vinogradov, Naomi Hsu, Steve Eberbach, Jeff Wenger

Funding agency:  NOAA Sea Grant

Project period:  July 2013 – January 2015 (completed)


Photograph of Philip Orton presenting at City Hall, at one of the public meetings where Jersey City Planners and Stevens Researchers presented options for reducing the chances of storm surge flooding.

Coastal cities across the country are weighing their options for adapting to rising floods, yet there is limited quantitative information available to help make these decisions. This project was a collaboration between coastal flooding scientists and Jersey City planners to develop and test several options for adapting the region’s urban coasts to flooding and sea level rise. Jersey City (JC) is the second-most populous city in NJ, yet has 43% of its land within the new FEMA 100-year flood zones. We leveraged pre-existing storm surge modeling and flood zone mapping to quantify the performance of a set of storm surge protection measures for Jersey City.

Outcomes and outputs from the research included: (1) regional flood zone maps that account for future sea level rise and storm climatology changes, (2) model-based map animations of how floodwaters enter JC to help understand how the pathways can be blocked, (3) a report of a collaboratively determined set of coastal adaptation options, and their performance with sea level rise, (4) an outreach workshop where we presented the project’s results to additional regional stakeholders, and (5) a transferable, peer reviewed and published adaptation planning and evaluation framework. Lastly, and still an ongoing process, it is our goal to help Jersey City, and possibly additional area cities, to implement climate change planning policies to adapt to coastal flooding.

This framework can also be utilized for many other U.S. coastal regions – anywhere that hydrodynamic models are already being used to simulate storm surges or map flood zones. FEMA has embarked on an ambitious effort to re-evaluate the nation’s coastal flood zone maps, and many of these regional efforts are utilizing these models. Many areas also have storm surge forecast models in place that can be similarly used for adaptation studies.

Project Results Summary

Computer storm surge simulations were used to map the effect of projected sea level rise on 100-year flood zones and to show the water pathways that flooded Jersey City during Hurricane Sandy, all useful information for planning measures that can prevent flooding.

Animation of modeled Hurricane Sandy flooding entering downtown Jersey City

Street-valley resolving animation of modeled Hurricane Sandy flooding entering downtown Jersey City (Blumberg et al. submitted). Color shading indicates floodwater depths over ground (legend on bottom right).

In several collaborative meetings, a broad set of realistic coastal protection measures and broad strategies were developed. Here is one example, a surge barrier that helps block a storm surge but could also be closed at low tide to create a rainwater basin for helping reduce the more frequent problem of rainfall flooding at high tide.

Illustration of one of 27 flood protection components, a surge barrier at the Tidewater Basin, south of downtown Jersey City

Illustration of one of 27 flood protection components, a surge barrier at Morris Canal Basin (aka Tidewater Basin), south of downtown Jersey City

This image comes from a partner project by Michael Baker Jr. Inc, and the report for that project is available here and includes both visualizations of the adaptation strategies, as well as a scoping study of what would be needed to conduct a benefit-cost analysis for the plans.

The storm surge modeling was then used to evaluate the efficacy of each adaptation measure, as well as how sea level rise and climate change will affect performance.  A city-wide adaptation scenario that combines several of the individual adaptation measures is found to protect most areas of the city from all storm events tested, ranging from a severe nor’easter that occurred in 1992, to Hurricane Sandy plus 31” of sea level rise (a high-end projection for 2055).


Flood elevation model results for Hurricane Sandy Control (left), the full adaptation scenario (center), and the difference. In the right‐side panel, white areas have flooding in the control run, and do not have flooding with the adaptation scenario (flooding is prevented).

Hurricanes of a higher flood level than Sandy are possible, though unlikely – based on our replication of the FEMA flood mapping study (with added sea level rise), the 14-foot protection elevation could be overtopped by storms today, with an annual probability of 0.3%, or by storms after 31” of sea level rise, with an annual probability of 1%. A partial adaptation plan of land elevation increases around planned projects leads to prevention of flooding for most neighborhoods for the #2 and #3 largest flood events of the past century, the 1992 nor’easter and Hurricane Donna, but does not provide protection against Hurricane Sandy, and only keeps certain neighborhoods dry for the other flood events (e.g. Donna) when we consider 31” of sea level rise.

Read the full report here.

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Climate Reconstruction for Long Island Sound Fisheries

Analyzing History to Project and Manage the Future: Simulating the Effects of Climate on Long Island Sound’s Physical Environment and Living Marine Resources

Lead PI:  Nickitas Georgas, Stevens Institute of Technology

Co-PIs:  Philip Orton, Alan Blumberg, Stevens Institute of Technology

Co-PI:  Penelope Howell, Connecticut Department of Energy and Environmental Protection

Associate Investigator:  Vincent Saba, Geophysical Fluid Dynamics Laboratory and NOAA National Marine Fisheries Service

Funding:  EPA Long Island Sound office, New York and Connecticut Sea Grant programs

In this project, we will a) conduct a multi-decadal three-dimensional hindcast of Long Island Sound (LIS) to study hypothesized linkages between the Sound’s physical climate and its recent ecological response and b) project future impacts of climate change and variability on the LIS ecosystem and its living marine resources over the span of the 21st century through model development and synthesis.

NYHOPS 3D model domain showing simulated SST, surface currents, and wind barbs. From the Google Earth viewer of the NYHOPS operational forecasts www.stevens.edu/NYHOPS

Figure 1: NYHOPS 3D model domain showing simulated SST, surface currents, and wind barbs. From the Google Earth viewer of the NYHOPS operational forecasts.

Specifically, our objectives are to:

  1. Address the paucity of physical environmental data during Long Island Sound’s (LIS) observed warming trend and accompanying fisheries shift since the 1970s by running a hindcast of the LIS circulation using the New York Harbor Observing and Prediction System (NYHOPS), an operational, comprehensive, high-resolution, three-dimensional, numerical model (Figures 1-2).
  2. Explore climate-forced links between the physical and ecological environment of the Sound by studying the statistical correlations of historic ecological data (such as the fish trawl survey data) to the physical environmental data from the NYHOPS model with a goal to explain the recent ecological regime changes and,
  3. Project the impacts of climate change and variability on the Sound’s ecosystem and its living marine resources until the year 2100, by forcing NYHOPS with Intergovernmental Panel for Climate Change (IPCC)-class global climate models, creating NYHOPS-based predictions for LIS to the end of this century, and deducing future changes to the LIS ecological regimes.
Figure 2. A zoom of the NYHOPS domain that covers the Long Island Sound. Shown is simulated SST (colored background and legend on the upper left), a popup with data from a UCONN buoy used in the NYHOPS model, and instantaneous surface current vectors also from the NYHOPS model. Screenshot taken from the NYHOPS google earth viewer 9/26/2012 1900Z.

Figure 2. A zoom of the NYHOPS domain that covers the Long Island Sound. Shown is simulated SST (colored background and legend on the upper left), a popup with data from a UCONN buoy used in the NYHOPS model, and instantaneous surface current vectors also from the NYHOPS model. Screenshot taken from the NYHOPS google earth viewer 9/26/2012 1900Z.


Over the last few decades, the LIS ecosystem has undergone profound changes. Water temperature measurements at a LIS long-term station frequently used in ecosystem assessments (LISS 2010, Howell and Auster 2012, among others) have recorded a significant warming trend (1.46ºC increase from 1976 to 2010; Dominion Resources Services 2011). Concurrently, substantial changes have occurred in the community structure and abundance of living marine resources in LIS (Howell et al 2005; Howell and Auster 2012). A dramatic example is the American lobster (Homarus Americanus) collapse, initiated by the major die-off in 1999.  Although multiple factors may have been synergistically responsible for this collapse, the increase in bottom temperature was likely the major factor that caused an increase in the mortality rate of lobsters, especially egg-bearing females (Howell et al 2005). Interestingly, the lobster collapse was exclusive to southern New England waters south of Cape Cod. The lobster stocks and fisheries further north, particularly the Gulf of Maine, are thriving. Reported landings have been at record highs over the past decade (Thunberg 2007). Based on the CT DEEP trawl survey, there seems to have been a shift in adult lobster population (ALTC 2010), that has altered the area where young lobsters recruit (Kim McKown, pers. comm.).

Fisheries-independent trawl surveys in LIS have reported substantial changes in finfish community structure and abundance (Howell and Auster 2012). Correlated with the increase in the bottom temperature of LIS from 1984 to 2008, the seasonal mean catch of cold-adapted finfish [i.e. windowpane flounder (Scophthalmus aquosus), spotted hake (Urophycis regia)] has significantly decreased, while warm-adapted species [i.e. butterfish (Peprilus triacanthus), striped sea robin (Prionotus evolans)] have increased (Howell and Auster 2012). There appears to have been a cold to warm species regime shift in the 95 finfish species examined statistically separating the community seen in 1984-1998 compared to 1999-2008 (Howell and Auster 2012). Although this time-period may be too short to attribute to climate change, it is apparent that the ecosystem of LIS may have responded to a climate perturbation.

The aforementioned reports suggest a regime shift in both the climate and ecosystem of LIS occurring around 1998. Remarkably, there have been increasingly more studies reporting a 1998 regime shift in the climate and living marine resources of coastal and pelagic marine ecosystems in vastly different parts of the world. To name a few, these include the Bering Sea (Rodionov and Overland 2005), the North Pacific (Overland et al 2008), and the North Sea (Weijerman et al 2005). Therefore, there may be a large-scale climate teleconnection between the local LIS climate and the global climate, whether due to natural or anthropogenic climate perturbations.

The apparent sensitivity of LIS to climate warrants research that elucidates the specific processes that are associated with the ecosystem’s response to climate perturbations. This is especially critical for projecting the impacts of global climate change on the LIS ecosystem given the 2-3ºC increase in surface air temperature projected by climate models included in the IPCC fourth assessment report (Christensen et al 2007). In order to assess, understand, and project the biophysical and mechanistic underpinnings between climate and living marine resources of  LIS, a detailed, historical analysis of climate and living marine resources is first required. However, the historical three-dimensional physical data of LIS is very sparse and only provides a general warming trend based on a few stations (one of which is near a power plant) without details on the relationships between circulation, hydrology, high-resolution depth-profile data covering the entire area of LIS, and interaction with the shelf-waters outside of LIS. Our proposed research will attempt to fill in these gaps.

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